Senior Machine Learning / Data Scientist

Hewlett Packard; Barueri; Presencial; BRL 200.000 - 300.000; Tempo integral

Resumo da oferta

A leading technology company in Brazil is seeking an experienced data science leader to manage complex projects, uncover insights from data, and guide teams in machine learning applications. The ideal candidate should have over ten years of relevant experience with strong expertise in statistical modeling and a four-year degree in a related field. This role focuses on driving innovation through data-driven solutions and requires excellent communication and leadership skills.

Qualificações

• Ten or more years of experience in data analytics or machine learning.
• Significant expertise in building systems using machine learning techniques.
• Strong communication skills for leadership and mentoring.

Responsabilidades

• Lead teams in complex data science projects.
• Develop models to extract valuable business insights.
• Prepare and present findings in industry conferences.

Conhecimentos

Machine learning

Data mining

Statistical modeling

Software development in Python

Cloud deployments on AWS/Azure

Formação académica

Four-year Degree in Mathematics, Statistics, Economics, Computer Science, Data Science

Ferramentas

Python

Pytorch

Tensorflow

SQL

Descrição da oferta de emprego

Job Summary

HP R&D Brazil is HPs premier research & development organization in Brazil.

Responsibilities

• Leads organization wide team or teams of other data science professionals in complex projects to mine data using modern tools and programming languages.
• Defines models to uncover patterns and predictions creating business value and innovation.
• Manages and creates relationships with business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects / initiatives.
• Ties insights into effective visualizations communicating business value and innovation potential.
• Works with various stakeholders, including business leaders, engineers, product managers, and data analysts, to identify business problems and develop data-driven solutions.
• Prepares and presents literature, presentations, invention disclosures for peer review & publication in industry data science domain initiatives and conferences.
• Assures insights are communicated regularly and effectively, reviewing designs, models and data compliance.
• Defines, communicates and drives data insights / innovation into the business.
• Leverages recognized domain expertise, business acumen, and overall data systems leadership to influence decisions of executive business leadership, development partners, and industry standards groups.
• Provides guidance, training and mentoring to less experienced staff members.

Education & Experience Recommended

• Four-year or Graduate Degree in Mathematics, Statistics, Economics, Computer Science, Data Science, or any other related discipline or commensurate work experience or demonstrated competence.
• Typically 10+ years of work experience, preferably in data analytics, statistical modeling, machine learning, or a related field.

Preferred Certifications

• Programming Language / s Certification (SQL, Python, or similar)

Knowledge & Skills

• Broad knowledge of machine learning, statistical modeling and data mining
• Expertise with building robust systems based on machine learning techniques.
• Track record of work in Generative AI and Machine Learning (LLMs, LVMs, LMMs, LAM, NEURO SYMBOLIC, SAM) development and deployment.
• Knowledge of cloud deployments on AWS / Azure
• Experience leveraging models from repositories such as Hugging Face
• Experience with deep learning frameworks such as Pytorch and Tensorflow.
• Excellent Software development skills with fast prototyping in Python.

Cross-Org Skills

• Technical leadership
• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity

Impact & Scope

• Impacts multiple teams and may act as a team or project leader providing direction to team activities and facilitates information validation and team decision making process.

Complexity

• Responds to moderately complex issues within established guidelines.